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  <div class="headertitle"><div class="title">Unsupervised Trainers</div></div>
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<a name="details" id="details"></a><h2 class="groupheader"> </h2>
<p>Optimized algorithms to solve specialized unsupervised optimization problems. </p>
<p>A supervised problem consists only of input data. Typical tasks are normalization distribution learning </p>
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Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_unsupervised_trainer.html">shark::AbstractUnsupervisedTrainer&lt; Model &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Superclass of unsupervised learning algorithms.  <a href="classshark_1_1_abstract_unsupervised_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_abstract_weighted_unsupervised_trainer.html">shark::AbstractWeightedUnsupervisedTrainer&lt; Model &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Superclass of weighted unsupervised learning algorithms.  <a href="classshark_1_1_abstract_weighted_unsupervised_trainer.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_normalize_components_unit_interval.html">shark::NormalizeComponentsUnitInterval&lt; DataType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Train a model to normalize the components of a dataset to fit into the unit inverval.  <a href="classshark_1_1_normalize_components_unit_interval.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_normalize_components_unit_variance.html">shark::NormalizeComponentsUnitVariance&lt; DataType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Train a linear model to normalize the components of a dataset to unit variance, and optionally to zero mean.  <a href="classshark_1_1_normalize_components_unit_variance.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_normalize_components_whitening.html">shark::NormalizeComponentsWhitening</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Train a linear model to whiten the data.  <a href="classshark_1_1_normalize_components_whitening.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_normalize_components_z_c_a.html">shark::NormalizeComponentsZCA</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Train a linear model to whiten the data.  <a href="classshark_1_1_normalize_components_z_c_a.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_normalize_kernel_unit_variance.html">shark::NormalizeKernelUnitVariance&lt; InputType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the scaling factor of a <a class="el" href="classshark_1_1_scaled_kernel.html" title="Scaled version of a kernel function.">ScaledKernel</a> so that it has unit variance in feature space one on a given dataset.  <a href="classshark_1_1_normalize_kernel_unit_variance.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_one_class_svm_trainer.html">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Training of one-class SVMs.  <a href="classshark_1_1_one_class_svm_trainer.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classshark_1_1_p_c_a.html">shark::PCA</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Principal Component Analysis.  <a href="classshark_1_1_p_c_a.html#details">More...</a><br /></td></tr>
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